Search Results (1,959)

Software quality assessment in agile projects remains fragmented. Technical, process-related, and team-related indicators are often evaluated through separate models, tools, and reports. This fragmentation limits cross-project comparability and weakens evidence-based decisions for software quality improvement. To address this problem, this study proposes the Overall Software Quality Index (OSQI), a multidimensional decision-support framework for software quality assessment in agile projects. OSQI integrates code quality, process quality, and team quality into a single project-level assessment model. The framework was initially grounded in ISO/IEC 25010:2011 and is discussed in relation to the ISO/IEC 25010:2023 revision, particularly its explicit inclusion of Safety as a product quality characteristic. Since the industrial datasets used in this study were not collected from safety-critical systems, Safety was not modeled as a separate OSQI dimension in the current version; instead, it is addressed as a scope limitation and future extension. The measurement structure was defined using the Goal–Question–Metric (GQM) approach. An initial set of 49 candidate metrics was reduced to 15 core indicators. This reduction was performed using dimension-specific strategies: Random Forest-based feature importance for code quality, Delphi and Analytic Hierarchy Process (AHP) for process quality, and thematic consolidation for team quality. The selected indicators were normalized and integrated through entropy-based weighting. This process generates an interpretable composite quality score. The main contribution of OSQI is not the isolated use of these methods, but their integration into a reproducible and tool-supported framework. The framework converts heterogeneous software engineering signals into a unified decision-support index. OSQI was evaluated using industrial agile project data. The data included static code analysis outputs, issue-tracking records, team assessment results, and product outcome indicators. In an exploratory validation across five industrial projects, OSQI showed a strong positive association with Net Promoter Score ($r=0.97, p=0.0076$) and a strong negative association with churn rate ($r=-0.97, p=0.0061$). A supporting software tool was also developed to automate data integration, score calculation, visualization, and project-level comparison. The findings suggest that OSQI can support quality monitoring, project benchmarking, and evidence-based improvement decisions in agile software engineering contexts. Full article

Background and Objectives: Water polo (WP) is a high-intensity, intermittent aquatic team sport that has been extensively investigated within sports science. While contemporary literature has examined the body composition and morphological characteristics of elite and international WP players, this study aimed to define the general body composition profile of world-class WP players and determine position-specific differences. Methods: The study involved 72 national team players from Serbia, Croatia, Greece, and Italy who participated in the Olympic Games, World Championships, or European Championships. Participants’ body composition was measured using the InBody 720 multichannel bioimpedance method. Ten different variables were examined to assess body structure regarding contractile and ballast components. Results: MANOVA revealed statistically significant differences in body composition across playing positions (Wilks’ lambda = 0.239, p < 0.000, η²_p = 0.402). The variables that had the greatest impact on the difference were: body mass, body fat and body mass index with the 47.0, 44.4, and 43.7% of explained total variance of the impact on the differences (p = 0.000), respectively. Conclusions: world-class WP players assigned to different playing positions differ significantly in body composition. These positional profiles should be considered in talent identification, selection procedures, training, and nutritional strategies to optimize performance models, considering the future evolution of the game at the highest competitive level. Coaches could use this information to initially select players for different specific positions based on anthropometric and body composition criteria. Full article

Background/Objectives: Papua New Guinea has a population of over 10 million, with its public cardiac surgical service provided by only one tertiary center. Despite the climbing burden of ischemic heart disease, no CABG operation has been performed before 2025 due to limited local surgical capacity. An international collaboration was planned in order to launch a CABG program in the country. Methods: Three cases were shortlisted after a multidisciplinary team discussion. A team-based “On-the-job” mentoring strategy was employed to facilitate skill transfer. The operation was carried out in a “twinning” fashion, with each role of the surgical team being taken up by “a pair”—the trainer (visiting team) and the learner (local team). The trainer demonstrated key skills and tips in the first case, and the “pair” switched positions in the following cases to maximize hands-on learning. The last case was performed entirely by the local team. Results: Three patients underwent CABG operations in this pilot program. A total of 2.33 grafts/case were performed on average, with no 30-day mortality. There were no major complications except for one patient developing right middle cerebral artery infarct on postoperative day 5. The patient was discharged one month later after achieving functional recovery and was started on anticoagulation therapy. Conclusions: International collaborations with strategic planning can play a critical role in starting new cardiac surgical programs in low–middle-income countries, with acceptable surgical outcomes. History has been made with the first-ever CABG operation successfully performed in Papua New Guinea. The journey ahead to sustain local cardiac surgical capacity and to provide safe and accessible cardiac surgical care for the country remains challenging. Full article

Background/Objectives: Caffeinated chewing gum is a practical, rapidly absorbed ergogenic aid increasingly used in team sports, yet its interaction with different small-sided soccer game (SSG) formats in young male players remains unclear. This study evaluated the effects of acute caffeinated (CAF) chewing gum on psychophysiological responses and kinematic profiles during intermittent (INT) and continuous (CON) 3-a-side SSGs. Methods: Twenty-four young male soccer players (18.4 ± 0.5 years) completed four 3-a-side SSG sessions separated by 48 h in a randomized, double-blind, placebo (PLA)-controlled, crossover design (CAF-INT, PLA-INT, CAF-CON, PLA-CON). Participants chewed 300 mg of CAF or PLA gum for 5 min, with mastication completed 5 min before warm-up session. The heart rates and kinematic profiles were recorded during the SSGs, and the ratings of perceived exertion (RPE), exercise enjoyment scale (EES), and visual analogue scale (VAS) to perceived mental fatigue (MF) were assessed post-game. Results: Compared with the PLA, the CAF increased the heart rate responses (HR), EES, total distance (TD), player load (PL), acceleration (ACC), and distances covered in selected speed zones (from Z0 to Z5), while reducing the RPE and MF. Significant format × supplementation interactions indicated that CAF-induced changes in high-intensity kinematic outcomes (TD, PL, ACC, Z2–Z5) and HR responses (HR_mean, HR_max) were generally greater in INT, whereas CAF-induced increases in low-intensity running distances (Z0 and Z1) and %HR_max were more pronounced in the CON format (all p < 0.05 for the reported effects; ${\eta }_p^2$ = 0.16–0.93 for CAF main effects [large effects]). The EES improvements were more pronounced in the CON format, whereas the MF and RPE reductions were more pronounced in the INT format. Conclusions: CAF chewing gum may be a practical acute strategy for modulating psychophysiological responses and kinematic profiles during SSGs, with the effects depending partly on the game format. Full article

Background: Accurate preoperative risk stratification of intraductal papillary mucinous neoplasms (IPMNs) remains a major challenge in pancreatic surgery. Cytology obtained through endoscopic ultrasound-guided fine needle aspiration (EUS-FNA) demonstrates high specificity but limited sensitivity, whereas molecular analysis of cyst fluid—particularly KRAS and GNAS mutations—has emerged as a promising complementary diagnostic tool. Methods: We conducted a narrative review combined with a retrospective single-center observational study of patients evaluated for suspected IPMN between 2018 and 2025 who underwent EUS-FNA with cytology and KRAS/GNAS testing followed by surgical resection. Histology was used as the reference standard. Given the limited number of resected cases (n = 25), results should be interpreted with caution. Results: A total of 105 patients were included, of whom 70 underwent EUS-FNA and 25 surgical resection. Final histology showed low-grade dysplasia in 12 cases (48%) and high-grade dysplasia in 13 cases (52%), with no invasive carcinoma detected, limiting the evaluation of diagnostic performance for invasive disease. Cytology demonstrated a sensitivity of 38.5% and specificity of 75% for advanced neoplasia. Molecular testing achieved 100% sensitivity but low specificity. A combined diagnostic strategy increased sensitivity to 92.3% compared with 38.5% for cytology alone, although with reduced specificity. Conclusions: A multimodal diagnostic approach integrating morphology, cytology, and molecular testing improves risk stratification of IPMNs and may supports surgical decision-making within multidisciplinary pancreatic teams, particularly in indeterminate cases, although its impact should be interpreted in the context of limited sample size. Full article

Artificial intelligence (AI) is increasingly being integrated into Clinical Decision-Support Systems (CDSSs), shifting attention from algorithmic performance alone to the broader sociotechnical conditions that shape effective human–AI collaboration. In this study, we investigated whether nine displacement-based structured coordination protocols can improve the collective diagnostic decision-making of hybrid human–AI teams (16 board-certified radiologists and a simulated AI model) in a radiological double-reading task for vertebral fracture detection from X-ray images. Among the protocols tested, the Accuracy-Oriented, Confidence-Oriented, and Presumptuous strategies achieved the highest (balanced) accuracy overall, with up to 97% among strong clinicians and 92% among weak ones, significantly outperforming simpler methods like majority voting. Conversely, approaches optimized for a single metric (e.g., sensitivity or specificity) introduced performance trade-offs. Benefits were strongest among less proficient clinicians, which exhibited substantial and consistent improvements, while proficient clinicians showed limited gains and occasional declines. Critically, Kasparov’s Law emerged as a comparative framework for empirically evaluating coordination quality relative to the diagnostic task, clinical objective, and clinician proficiency by identifying situations in which less proficient clinicians supported by superior coordination protocols outperformed more proficient clinicians operating under inferior ones. These findings demonstrate that coordination design is a critical determinant of hybrid human–AI decision-making, highlighting that a well-structured process can be more relevant than individual components’ performance and support process-centered approaches to the development and evaluation of CDSSs. Full article

Objectives: To describe the scientific evidence regarding adjuvant treatment for stage III and IV cutaneous melanoma and the unresolved issues in this setting. Methods: This review examines the main studies on adjuvant medical therapies approved over the years by the Food and Drug Administration and European Medicines Agency together with the main evidence related to the treatments referred to in the National Comprehensive Cancer Network and European Society of Clinical Oncology guidelines at the time of submission (May 2026) for stage III and IV cutaneous melanoma. A particular focus on immunotherapy (interferon, ipilimumab, and anti-PD-1 antibodies, both as monotherapy and in combination) and targeted therapy with anti-BRAF agents, either as monotherapy or in combination with MEK inhibitors, is given. Besides that, this work also evaluates the role of radiation therapy and addresses some unresolved issues, such as adjuvant therapy in stage IIIA and treatment selection in BRAF-mutated melanoma. Results: Adjuvant therapy for stage III and IV cutaneous melanoma has evolved over the years, starting with interferon and progressing to the use of immunocheckpoint inhibitors and targeted therapy. However, not all treatments that have proven effective in metastatic disease have subsequently played a role in the adjuvant setting. Conclusions: Currently, adjuvant treatment for stage III and IV cutaneous melanoma involves the use of anti-PD-1 antibodies (nivolumab and pembrolizumab) and dabrafenib plus trametinib if the patient has a BRAF V600 mutation. It was not possible to identify the adjuvant therapy of choice for BRAF-mutated melanoma, and several factors must be considered when deciding between immunotherapy and targeted therapy. The role of radiation therapy remains controversial and could be discussed by the multidisciplinary team as part of the adjuvant strategy in selected patients. Likewise, adjuvant therapy for stage IIIA melanoma should be carefully evaluated in light of the risk–benefit ratio. Full article

Opioid misuse continues to be a major public health issue in the United States. Older adults (≥65) are at particular risk of harm from opioids due to changes in opioid pharmacokinetics with age; however, healthcare professionals lack training and confidence in addressing opioid harm reduction strategies in this population. Therefore, the purpose of this study was to improve healthcare professional knowledge and beliefs regarding opioid harm reduction strategies amongst older adults. An 8 h interprofessional conference was conducted 1 May 2025 to educate healthcare providers about opioid misuse prevention strategies for older adults. This study utilized a quasi-experimental one-group pretest–posttest design to assess changes in healthcare professional knowledge and beliefs before and after the conference. Healthcare professionals in the U.S. were recruited to participate in the conference via email listservs with national reach, predominantly concentrated in Alabama. Data were collected at pre- and post-conference via an anonymous online survey informed by the Theory of Planned Behavior and Health Belief Model. Primary outcome measures included: (1) knowledge of opioid use and misuse in older adults (5 items); (2) prescribing and dispensing attitudes surrounding opioids and medications for opioid use disorder (MOUD) (5 items); (3) perceived susceptibility to harm from opioids (4 items); and (4) perceived barriers to opioid harm reduction in older adults (17-items). Constructs were measured using multiple-choice questions (knowledge) and Likert-type scales (1 = strongly disagree, 5 = strongly agree). Secondarily, intention to join a Microsoft Teams working group for ongoing collaboration was assessed through a single categorical (Yes/No/Unsure) multiple-choice question at post-conference. Data were analyzed using descriptive statistics, and differences in mean knowledge, attitudes, susceptibility, and barriers scale scores from pre- to post-conference were analyzed using Wilcoxon signed-rank tests (alpha = 0.05). Of N = 75 survey respondents, the majority were White (86.7%), female (74.7%), 50 years of age on average, and employed as pharmacists (68%). Overall, mean (SD) knowledge (83.73% [19.92] versus 90.67% [12.45]; p = 0.011) and perceived susceptibility (3.82 [0.63] versus 4.03 [0.63]; p = 0.002) increased from pre- to post-conference, while perceived barriers decreased (2.71 [0.54] versus 2.54 [0.58]; p = 0.001). Despite an upward trend, there was no statistically significant change in the mean prescribing and dispensing attitudes from baseline to post-conference. Additionally, 34.7% intended to join the Microsoft Teams working group at post-conference. Findings support the utility of interprofessional educational interventions to increase healthcare provider knowledge and beliefs regarding opioid harm reduction strategies amongst older adults. Full article

Addressing bidirectional section disruptions in urban rail transit, this paper proposes a fault recovery strategy that explicitly incorporates the constraints imposed by train operation intersections (i.e., turn-back stations). To achieve this goal, this study develops a resilience-oriented recovery framework that captures operational dependencies associated with turn-back sections, compares recovery outcomes under three designed failure scenarios with and without train operation adjustment, and evaluates how variations in the number of repair teams affect resilience loss, recovery time, and repair priorities. Using the Chengdu Metro network as a case study, the results show that, compared with strategies that do not consider turn-back operation adjustment, the proposed method reduces resilience loss by 17.9%, 16.0%, and 38.6% across the three scenarios. The results also indicate that increasing the number of repair teams shortens total recovery time and reduces resilience loss, although the marginal improvement gradually decreases. For example, in Scenario 1, resilience loss decreases from 2.3% to 0.7%, while total recovery time is reduced from 13.4 to 3.4. The main contribution of this study is the integration of turn-back-section dependency and repair-team constraints into a unified resilience-based recovery framework, which may serve as a reference for post-disruption recovery planning in urban rail transit systems. Full article

To address the limitations of the centralized hydraulic steering system used in the first-generation heavy-duty wheeled platform developed by our team, this study proposes a fully electrified steering system based on a compact direct-drive electro-mechanical actuator (DEMA) architecture. Compared with the original hydraulic system, the proposed solution reduces the steering-system weight from approximately 150 kg to 32 kg in the single-channel configuration and 40 kg in the dual-channel configuration, while significantly improving system integration and maintainability. For the single-channel DEMA steering system, a composite control strategy combining three-loop PID control with feedforward compensation is developed to improve dynamic response and position-tracking accuracy. AMESim simulation results under a steering resistance torque of 6000 ± 500 Nm show that the system achieves an overshoot below 2%, a steady-state error below 0.1°, and a tracking error below 0.4°. To reduce motor power and thermal-management requirements, a dual-channel DEMA steering architecture is further proposed. Considering inter-channel parameter differences, a primary–secondary synchronization control strategy is developed to suppress force-fighting behavior and improve motion consistency. Simulation results demonstrate that the proposed strategy effectively reduces synchronization errors and maintains highly consistent force output between channels while preserving excellent steering accuracy and tracking performance. The proposed fully electrified steering system and synchronization control strategy provide an effective solution for improving the dynamic performance, lightweight design, and reliability of heavy-duty wheeled platforms. Full article

Background: Pediatric emergencies are high-risk clinical situations requiring timely, accurate, and coordinated interventions. Nurses play a pivotal role in early recognition and management of acute pediatric conditions; however, the rarity and complexity of these events often limit clinical exposure and preparedness. Continuous professional education is therefore essential to ensure patient safety and high-quality care. Objective: This systematic review aimed to synthesize evidence on innovative continuing education strategies for nurses involved in pediatric emergency care, with a primary focus on studies evaluating educational effectiveness and a secondary contextual focus on studies describing training needs, perceived barriers, preparedness, and implementation conditions. Methods: The review was conducted according to PRISMA guidelines. The protocol was registered in PROSPERO (ID CRD420251120993). A comprehensive search of PubMed, CINAHL Complete, Scopus, and the Cochrane Library identified studies published between 2015 and August 2025. Primary intervention studies were used to assess educational effectiveness, whereas descriptive, observational, qualitative, and review-based evidence was retained as contextual evidence. Methodological quality was assessed using Joanna Briggs Institute (JBI) tools. Results: Forty-nine studies met the inclusion criteria, including randomized controlled trials, quasi-experimental studies, observational and cohort studies, and integrative or narrative reviews. Educational interventions mainly involved simulation-based training, blended learning, telesimulation, digital education, and structured training programs. Intervention studies suggested improvements in knowledge, technical skills, self-efficacy, and team performance, while contextual studies highlighted training needs, perceived barriers, preparedness, and implementation challenges. However, the evidence was limited by methodological heterogeneity, frequent reliance on self-reported outcomes, and limited long-term follow-up. Conclusions: Simulation-based, blended, and telesimulation-based educational strategies may be associated with short-term improvements in nurses’ preparedness and educational outcomes in pediatric emergency care. However, conclusions regarding effectiveness should be interpreted cautiously because of methodological heterogeneity, reliance on subjective outcomes, and limited evidence on long-term clinical and patient-safety outcomes. Full article

This paper revisits Problem A of the TEAM 35 benchmark from the viewpoint of robustness estimation under manufacturing uncertainty. Rather than treating the original extremal-position-based sensitivity metric as the formulation to be improved, it is used only as a baseline for comparison with other metrics. In this work, robustness is evaluated as the largest degradation of the nominal magnetic-field homogeneity objective observed over prescribed sets of admissible manufacturing perturbations. In addition to turn-position uncertainties, the present study also includes uncertainty in the excitation current density. While turn-position errors affect each turn individually, current-density uncertainty affects the error contributions of all turns simultaneously through a common term. This common-mode excitation uncertainty represents an extension of the original benchmark formulation and is one of the paper’s main focal points. Several Design of Experiments (DoE) methodologies, as well as search-based robustness estimation strategies, are compared in terms of error in estimated robustness and computational demand. The results show that the original extremal-position-based approximation can substantially underestimate the sampled robustness of the nominal field-homogeneity objective. Including current-density uncertainty further increases the discrepancy between the original metric and the sampled robustness estimates. Full article

Background: Black Sub-Saharan African immigrants are among the fastest-growing immigrant populations in the United States, and their mental health needs, particularly with respect to depression, remain understudied. Cultural beliefs, linguistic frameworks, and coping practices in this population often diverge from Western psychiatric models, suggesting that conventional approaches may fail to capture how distress is experienced and expressed. Objective: This scoping review mapped literature on how Black Sub-Saharan African immigrant adults in the United States perceive, report, and respond to depression. Methods: Following PRISMA-ScR guidelines, six electronic databases were systematically searched for empirical studies published between 2000 and 2026. Two reviewers independently screened and extracted data using a standardized form. Data were analyzed using a narrative synthesis approach combining deductive thematic categorization across three predefined review domains with inductive identification of subthemes through iterative team discussion and consensus, with sociocultural, religious, linguistic, and structural factors examined as cross-cutting themes. Findings were synthesized narratively across three domains: perceptions of depression, reporting and communication, and responses to depression. Results: A total of 19 studies met the inclusion criteria (7 quantitative, 10 qualitative, 2 mixed methods; total N ≈ 1900), generating 24 themes. Perception themes highlighted cultural non-recognition of depression (12 of 19 studies), absence of equivalent terms in African languages (7 studies), spiritual explanatory models, and profound stigma. Reporting patterns showed predominant somatic symptom expression and very low disclosure to providers (2.6–4.2%), with depression prevalence ranging from 8.1% to 100% and no validated screening instrument identified for this population. Response themes emphasized religion and social support as primary coping strategies, with formal mental health utilization virtually absent due to structural, cultural, and intersectional barriers. Conclusions: Depression among Black Sub-Saharan African immigrants is widely experienced yet rendered invisible through interlocking cultural, linguistic, somatic, and institutional mechanisms, which this review terms an architecture of invisibility, leaving it largely unaddressed by formal mental health systems. The identification of only one intervention study underscores a substantial gap between documenting the burden of depression and advancing evidence-informed solutions. Culturally validated measures, faith-based intervention models, longitudinal designs, and attention to structural determinants are urgently needed. Full article

Machine learning (ML) methods for network anomaly detection are emerging as effective proactive strategies in threat hunting, substantially reducing the time required for threat detection and response. However, the challenges in training and maintaining ML models, coupled with frequent false positives, diminish their acceptance and trustworthiness. In response, Explainable AI (XAI) techniques have been introduced to enable cybersecurity operations teams to assess alerts generated by AI systems more confidently. Despite these advancements, XAI tools have encountered limited acceptance from incident responders and have struggled to meet the decision-making needs of both analysts and model maintainers. Large Language Models (LLMs) offer a unique approach to tackling these challenges. Through tuning, LLMs have the ability to discern patterns across vast amounts of information and meet varying functional requirements. In this research, we introduce the development of HuntGPT, a specialized intrusion detection dashboard created to implement a Random Forest classifier trained utilizing the KDD99 dataset. The tool incorporates XAI frameworks like SHAP and Lime, enhancing user-friendliness and intuitiveness of the model. When combined with a GPT-3.5 Turbo conversational agent, HuntGPT aims to deliver detected threats in an easily explainable format, emphasizing user understanding and offering a smooth interactive experience. We investigate the system’s comprehensive architecture and its diverse components, assess the prototype’s technical accuracy using the Certified Information Security Manager (CISM) Practice Exams, and analyze the quality of response readability across six unique metrics. Our results indicate that conversational agents, underpinned by LLM technology and integrated with XAI, can enable a robust mechanism for generating explainable and actionable AI solutions, especially within the realm of intrusion detection systems. Full article

This paper proposes a multi-criteria decision making (MCDM) model, namely, Weighted Product Evaluation Based on Distance from Average Solution (WPEDAS), to evaluate the financial performance of companies. The proposed WPEDAS model focuses on the weighted product approach, which is different from the existing Evaluation Based on Distance from Average Solution (EDAS) model that adopts a weighted sum approach based on distance from average solution. Besides that, we further enhance the model performance by developing a hybrid MCDM model. The proposed hybrid Weighted Aggregated Sum Product Evaluation Based on Distance from Average Solution (WASPEDAS) model is developed based on the weighted sum EDAS and the proposed WPEDAS. The proposed hybrid WASPEDAS model offers higher flexibility and robustness of customizing decision strategies based on the decision makers in solving MCDM problems. The proposed hybrid model is demonstrated using the financial ratios of companies in the Consumer Discretionary sector in the NASDAQ Exchange. The entropy weight method is integrated into the proposed models to determine the weights of decision criteria. Based on the results of sensitivity analyses, the proposed hybrid WASPEDAS model proves its reliability and robustness in performance evaluation. This implies that the proposed hybrid WASPEDAS model offers greater stability in ranking the companies, thus helping investors and fund managers in analyzing the companies during investment decision making. In addition, this study also provides guidance to the companies’ management teams in their strategic and tactical decision making to reduce volatility in driving the companies towards excellence. Full article